Salmon migration optimization: A novel nature-inspired algorithm

Abstract

This paper proposes a novel nature-inspired algorithm called salmon migration optimization (SMO). The main inspirations of this algorithm are based on the navigation methods of the salmon migration activity in the nature. Three heuristics in SMO, respectively called water flow-oriented heuristic (WFOH), magnetic-oriented heuristic (MOH), and pheromone-oriented heuristic (POH), are developed to make SMO has the capability of exploitation and exploration. Optimization results illustrate that SMO always obtains competitive solutions on most of test functions.